Results 21 to 30 of about 211,957 (254)

Implicit Semantic Data Augmentation for Hand Pose Estimation

IEEE Access, 2022
Data augmentation is a well-known technique used for improving the generalization performance of modern neural networks. After the success of several traditional random data augmentation for images (including flipping, translation, or rotation), a recent
Kyeongeun Seo, Hyeonjoong Cho, Daewoong Choi, Ju-Derk Park   +3 more
doaj   +1 more source

Designing Hand Pose Aware Virtual Keyboard With Hand Drift Tolerance

IEEE Access, 2019
An unintentional hand drift adversely affects the typing performance of conventional virtual keyboards. To overcome this, we proposed to utilize the typing patterns of skilled typists.
Daewoong Choi, Hyeonjoong Cho, Kyeongeun Seo, Sangyub Lee, Jaekyu Lee, Jaejin Ko   +5 more
doaj   +1 more source

Hand pose estimation based on improved NSRM network

EURASIP Journal on Advances in Signal Processing, 2023
Hand pose estimation is the basis of dynamic gesture recognition. In vision-based hand pose estimation, the performance of hand pose estimation is affected due to the high flexibility of hand joints, local similarity and severe occlusion among hand ...
Shiqiang Yang, Duo He, Qi Li, Jinhua Wang, Dexin Li   +4 more
doaj   +1 more source

Hands Deep in Deep Learning for Hand Pose Estimation

CoRR, 2015
We introduce and evaluate several architectures for Convolutional Neural Networks to predict the 3D joint locations of a hand given a depth map. We first show that a prior on the 3D pose can be easily introduced and significantly improves the accuracy and reliability of the predictions.
Markus Oberweger, Paul Wohlhart, Vincent Lepetit   +2 more
openaire   +2 more sources

Vision-Based Pose Estimation for Robot-Mediated Hand Telerehabilitation

Sensors, 2016
Vision-based Pose Estimation (VPE) represents a non-invasive solution to allow a smooth and natural interaction between a human user and a robotic system, without requiring complex calibration procedures.
Giuseppe Airò Farulla, Daniele Pianu, Marco Cempini, Mario Cortese, Ludovico O. Russo, Marco Indaco, Roberto Nerino, Antonio Chimienti, Calogero M. Oddo, Nicola Vitiello   +9 more
doaj   +1 more source

Hand Grasp Pose Prediction Based on Motion Prior Field

Biomimetics, 2023
Shared control of bionic robot hands has recently attracted much research attention. However, few studies have performed predictive analysis for grasp pose, which is vital for the pre-shape planning of robotic wrists and hands.
Xu Shi, Weichao Guo, Wei Xu, Xinjun Sheng   +3 more
doaj   +1 more source

A Robust Hand Pose Estimation Algorithm for Hand Rehabilitation [PDF]

, 2013
During a rehabilitation session, patient activity should be continuously monitored in order to correct wrong movements and to follow patient improvements. Therefore, the application of human motion tracking techniques to rehabilitation is finding more and more consensus.
Francesca Cordella, Francesco Di Corato, Loredana Zollo, Bruno Siciliano   +3 more
openaire   +2 more sources

Towards pen‐holding hand pose recognition: A new benchmark and a coarse‐to‐fine PHHP recognition network

IET Biometrics, 2022
Hand pose recognition has been one of the most fundamental tasks in computer vision and pattern recognition, and substantial effort has been devoted to this field. However, owing to lack of public large‐scale benchmark dataset, there is little literature
Pingping Wu, Lunke Fei, Shuyi Li, Shuping Zhao, Xiaozhao Fang, Shaohua Teng   +5 more
doaj   +1 more source

Using 3D Hand Pose Data in Recognizing Human–Object Interaction and User Identification for Extended Reality Systems

Information
Object detection and action/gesture recognition have become imperative in security and surveillance fields, finding extensive applications in everyday life.
Danish Hamid, Muhammad Ehatisham Ul Haq, Amanullah Yasin, Fiza Murtaza, Muhammad Awais Azam   +4 more
doaj   +1 more source

Back-Hand-Pose

Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology, 2020
The automatic recognition of how people use their hands and fingers in natural settings -- without instrumenting the fingers -- can be useful for many mobile computing applications. To achieve such an interface, we propose a vision-based 3D hand pose estimation framework using a wrist-worn camera.
Wu, E, Yuan, Y, Yeo, HS, Quigley, A, Koike, H, Kitani, KM   +5 more
openaire   +2 more sources